Decentralized Abstractions For Multi-Agent Systems Under Coupled Constraints

TL;DR

This paper develops a decentralized abstraction framework for multi-agent systems with coupled constraints, enabling high-level task planning through well-posed transition systems derived from system dynamics and discretization conditions.

Contribution

It introduces a novel decentralized abstraction method that accounts for coupled constraints and provides conditions for discretization ensuring meaningful transition systems.

Findings

Conditions for space and time discretization ensuring well-posed transition systems.

Design parameters enabling multiple transitions and motion planning.

Framework accommodates feedback interconnections and high-level task execution.

Abstract

The goal of this report is to define abstractions for multi-agent systems with feedback interconnection in their dynamics. In the proposed decentralized framework, we specify a finite or countable transition system for each agent which only takes into account the discrete positions of its neighbors. The dynamics of the considered systems consist of two components. An appropriate feedback law which guarantees that certain system and network requirements are fulfilled and induces coupled constraints, and additional free inputs which we exploit in order to accomplish high level tasks. In this work, we provide sufficient conditions on the space and time discretization for the abstraction of the system's behaviour which ensure that we can extract a well posed and hence meaningful transition system. Furthermore, these conditions include design parameters whose tuning provides the possibility for multiple transitions, and hence, enable the construction of transition systems with motion planning capabilities.